Change in COPD Assessment Test (CAT) score from a stable baseline has a high predictive capability for acute exacerbations

Background: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with high mortality, morbidity and a significant burden on people and healthcare systems. Identifying self-reported data that has predictive capacity for AECOPD may enable timely intervention and improved outcomes.

Methods: This Exploratory Data Analysis uses user-entered data from the myCOPD app (a digital therapeutic) to identify features capable of predicting AECOPD. 1,758 patient app users generated 193,597 records containing 3795 exacerbations. We engineered features based on measures from myCOPD. To establish the relative feature strength, we calculated feature importance using the AdaBoost algorithm and produced time-series analysis visualisations.